Overview

Dataset statistics

Number of variables45
Number of observations790215
Missing cells22102799
Missing cells (%)62.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory271.3 MiB
Average record size in memory360.0 B

Variable types

Numeric39
Unsupported1
Categorical5

Alerts

level_1 is highly correlated with ICULOSHigh correlation
SBP is highly correlated with MAP and 1 other fieldsHigh correlation
MAP is highly correlated with SBP and 1 other fieldsHigh correlation
DBP is highly correlated with SBP and 1 other fieldsHigh correlation
BaseExcess is highly correlated with HCO3 and 1 other fieldsHigh correlation
HCO3 is highly correlated with BaseExcess and 1 other fieldsHigh correlation
pH is highly correlated with BaseExcessHigh correlation
PaCO2 is highly correlated with HCO3High correlation
BUN is highly correlated with CreatinineHigh correlation
Creatinine is highly correlated with BUNHigh correlation
Bilirubin_direct is highly correlated with Bilirubin_totalHigh correlation
Bilirubin_total is highly correlated with Bilirubin_directHigh correlation
Hct is highly correlated with HgbHigh correlation
Hgb is highly correlated with HctHigh correlation
Unit1 is highly correlated with Unit2High correlation
Unit2 is highly correlated with Unit1High correlation
ICULOS is highly correlated with level_1High correlation
level_1 is highly correlated with ICULOS and 1 other fieldsHigh correlation
SBP is highly correlated with MAP and 1 other fieldsHigh correlation
MAP is highly correlated with SBP and 1 other fieldsHigh correlation
DBP is highly correlated with SBP and 1 other fieldsHigh correlation
BaseExcess is highly correlated with HCO3 and 1 other fieldsHigh correlation
HCO3 is highly correlated with BaseExcess and 1 other fieldsHigh correlation
pH is highly correlated with BaseExcessHigh correlation
PaCO2 is highly correlated with HCO3High correlation
BUN is highly correlated with Creatinine and 1 other fieldsHigh correlation
Creatinine is highly correlated with BUN and 1 other fieldsHigh correlation
Bilirubin_direct is highly correlated with Bilirubin_totalHigh correlation
Phosphate is highly correlated with BUN and 1 other fieldsHigh correlation
Bilirubin_total is highly correlated with Bilirubin_directHigh correlation
Hct is highly correlated with HgbHigh correlation
Hgb is highly correlated with HctHigh correlation
Unit1 is highly correlated with Unit2High correlation
Unit2 is highly correlated with Unit1High correlation
ICULOS is highly correlated with level_1 and 1 other fieldsHigh correlation
Sepsis is highly correlated with HoursHigh correlation
Hours is highly correlated with level_1 and 2 other fieldsHigh correlation
level_1 is highly correlated with ICULOSHigh correlation
SBP is highly correlated with MAPHigh correlation
MAP is highly correlated with SBP and 1 other fieldsHigh correlation
DBP is highly correlated with MAPHigh correlation
BaseExcess is highly correlated with HCO3 and 1 other fieldsHigh correlation
HCO3 is highly correlated with BaseExcessHigh correlation
pH is highly correlated with BaseExcessHigh correlation
BUN is highly correlated with CreatinineHigh correlation
Creatinine is highly correlated with BUNHigh correlation
Bilirubin_direct is highly correlated with Bilirubin_totalHigh correlation
Bilirubin_total is highly correlated with Bilirubin_directHigh correlation
Hct is highly correlated with HgbHigh correlation
Hgb is highly correlated with HctHigh correlation
Unit1 is highly correlated with Unit2High correlation
Unit2 is highly correlated with Unit1High correlation
ICULOS is highly correlated with level_1High correlation
Unit2 is highly correlated with Unit1High correlation
Unit1 is highly correlated with Unit2High correlation
HR has 61189 (7.7%) missing values Missing
O2Sat has 95079 (12.0%) missing values Missing
Temp has 523314 (66.2%) missing values Missing
SBP has 120201 (15.2%) missing values Missing
MAP has 80858 (10.2%) missing values Missing
DBP has 380297 (48.1%) missing values Missing
Resp has 77258 (9.8%) missing values Missing
EtCO2 has 790215 (100.0%) missing values Missing
BaseExcess has 707834 (89.6%) missing values Missing
HCO3 has 726598 (91.9%) missing values Missing
FiO2 has 678060 (85.8%) missing values Missing
pH has 699600 (88.5%) missing values Missing
PaCO2 has 720927 (91.2%) missing values Missing
SaO2 has 751055 (95.0%) missing values Missing
AST has 778395 (98.5%) missing values Missing
BUN has 725739 (91.8%) missing values Missing
Alkalinephos has 778683 (98.5%) missing values Missing
Calcium has 750897 (95.0%) missing values Missing
Chloride has 724438 (91.7%) missing values Missing
Creatinine has 737728 (93.4%) missing values Missing
Bilirubin_direct has 789033 (99.9%) missing values Missing
Glucose has 693559 (87.8%) missing values Missing
Lactate has 763072 (96.6%) missing values Missing
Magnesium has 728734 (92.2%) missing values Missing
Phosphate has 750319 (95.0%) missing values Missing
Potassium has 704379 (89.1%) missing values Missing
Bilirubin_total has 780522 (98.8%) missing values Missing
TroponinI has 789250 (99.9%) missing values Missing
Hct has 697157 (88.2%) missing values Missing
Hgb has 720394 (91.2%) missing values Missing
PTT has 751909 (95.2%) missing values Missing
WBC has 730867 (92.5%) missing values Missing
Fibrinogen has 784185 (99.2%) missing values Missing
Platelets has 738716 (93.5%) missing values Missing
Unit1 has 386165 (48.9%) missing values Missing
Unit2 has 386165 (48.9%) missing values Missing
EtCO2 is an unsupported type, check if it needs cleaning or further analysis Unsupported
level_1 has 20336 (2.6%) zeros Zeros
BaseExcess has 19355 (2.4%) zeros Zeros

Reproduction

Analysis started2021-11-29 18:19:15.205593
Analysis finished2021-11-29 18:21:09.485959
Duration1 minute and 54.28 seconds
Software versionpandas-profiling v3.1.1
Download configurationconfig.json

Variables

PatientID
Real number (ℝ≥0)

Distinct20336
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10192.65256
Minimum1
Maximum20643
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.0 MiB
2021-11-29T19:21:09.623765image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1019
Q15074
median10174
Q315284
95-th percentile19325
Maximum20643
Range20642
Interquartile range (IQR)10210

Descriptive statistics

Standard deviation5893.668065
Coefficient of variation (CV)0.5782271129
Kurtosis-1.198551555
Mean10192.65256
Median Absolute Deviation (MAD)5107
Skewness0.002769282249
Sum8054386946
Variance34735323.26
MonotonicityIncreasing
2021-11-29T19:21:09.890467image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3658336
 
< 0.1%
4905336
 
< 0.1%
8132336
 
< 0.1%
16581336
 
< 0.1%
18469336
 
< 0.1%
18823335
 
< 0.1%
14462334
 
< 0.1%
5359330
 
< 0.1%
6507328
 
< 0.1%
16575305
 
< 0.1%
Other values (20326)786903
99.6%
ValueCountFrequency (%)
154
 
< 0.1%
223
 
< 0.1%
348
 
< 0.1%
429
 
< 0.1%
548
 
< 0.1%
617
 
< 0.1%
745
 
< 0.1%
840
 
< 0.1%
9258
< 0.1%
1023
 
< 0.1%
ValueCountFrequency (%)
2064333
 
< 0.1%
2064242
 
< 0.1%
2064121
 
< 0.1%
2064025
 
< 0.1%
2063926
 
< 0.1%
2063841
 
< 0.1%
20637142
< 0.1%
2063643
 
< 0.1%
2063542
 
< 0.1%
2063420
 
< 0.1%

level_1
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
ZEROS

Distinct336
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean25.33244497
Minimum0
Maximum335
Zeros20336
Zeros (%)2.6%
Negative0
Negative (%)0.0%
Memory size6.0 MiB
2021-11-29T19:21:10.163238image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q19
median20
Q333
95-th percentile60
Maximum335
Range335
Interquartile range (IQR)24

Descriptive statistics

Standard deviation27.95415975
Coefficient of variation (CV)1.103492371
Kurtosis23.91437157
Mean25.33244497
Median Absolute Deviation (MAD)12
Skewness3.999242411
Sum20018078
Variance781.4350476
MonotonicityNot monotonic
2021-11-29T19:21:10.632622image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
020336
 
2.6%
120336
 
2.6%
220336
 
2.6%
320336
 
2.6%
420336
 
2.6%
520336
 
2.6%
620336
 
2.6%
720336
 
2.6%
820212
 
2.6%
920090
 
2.5%
Other values (326)587225
74.3%
ValueCountFrequency (%)
020336
2.6%
120336
2.6%
220336
2.6%
320336
2.6%
420336
2.6%
520336
2.6%
620336
2.6%
720336
2.6%
820212
2.6%
920090
2.5%
ValueCountFrequency (%)
3355
< 0.1%
3346
< 0.1%
3337
< 0.1%
3327
< 0.1%
3317
< 0.1%
3307
< 0.1%
3298
< 0.1%
3288
< 0.1%
3279
< 0.1%
3269
< 0.1%

HR
Real number (ℝ≥0)

MISSING

Distinct333
Distinct (%)< 0.1%
Missing61189
Missing (%)7.7%
Infinite0
Infinite (%)0.0%
Mean84.98526445
Minimum20
Maximum280
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.0 MiB
2021-11-29T19:21:10.917784image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum20
5-th percentile60
Q173
median84
Q396
95-th percentile114
Maximum280
Range260
Interquartile range (IQR)23

Descriptive statistics

Standard deviation16.94043114
Coefficient of variation (CV)0.1993337463
Kurtosis0.4346089689
Mean84.98526445
Median Absolute Deviation (MAD)11
Skewness0.4188687253
Sum61956467.4
Variance286.9782073
MonotonicityNot monotonic
2021-11-29T19:21:11.181301image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8024652
 
3.1%
8818653
 
2.4%
9017764
 
2.2%
8416391
 
2.1%
8216116
 
2.0%
7015905
 
2.0%
8715698
 
2.0%
8515629
 
2.0%
8115614
 
2.0%
8615224
 
1.9%
Other values (323)557380
70.5%
(Missing)61189
 
7.7%
ValueCountFrequency (%)
2012
< 0.1%
211
 
< 0.1%
224
 
< 0.1%
22.51
 
< 0.1%
232
 
< 0.1%
241
 
< 0.1%
255
< 0.1%
262
 
< 0.1%
26.52
 
< 0.1%
278
< 0.1%
ValueCountFrequency (%)
2802
< 0.1%
2651
< 0.1%
2601
< 0.1%
2231
< 0.1%
2211
< 0.1%
2191
< 0.1%
2161
< 0.1%
2101
< 0.1%
2011
< 0.1%
2001
< 0.1%

O2Sat
Real number (ℝ≥0)

MISSING

Distinct143
Distinct (%)< 0.1%
Missing95079
Missing (%)12.0%
Infinite0
Infinite (%)0.0%
Mean97.26568772
Minimum20
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.0 MiB
2021-11-29T19:21:11.446832image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum20
5-th percentile93
Q196
median98
Q399.5
95-th percentile100
Maximum100
Range80
Interquartile range (IQR)3.5

Descriptive statistics

Standard deviation2.908793658
Coefficient of variation (CV)0.02990565045
Kurtosis66.56344143
Mean97.26568772
Median Absolute Deviation (MAD)2
Skewness-4.570024911
Sum67612881.1
Variance8.461080544
MonotonicityNot monotonic
2021-11-29T19:21:11.716113image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100169879
21.5%
9896045
12.2%
9991092
11.5%
9790633
11.5%
9676519
9.7%
9556184
 
7.1%
9435715
 
4.5%
9320942
 
2.7%
9211948
 
1.5%
99.56384
 
0.8%
Other values (133)39795
 
5.0%
(Missing)95079
12.0%
ValueCountFrequency (%)
202
 
< 0.1%
212
 
< 0.1%
225
< 0.1%
232
 
< 0.1%
243
< 0.1%
254
< 0.1%
264
< 0.1%
277
< 0.1%
286
< 0.1%
293
< 0.1%
ValueCountFrequency (%)
100169879
21.5%
99.56384
 
0.8%
99.41
 
< 0.1%
99.21
 
< 0.1%
9991092
11.5%
98.55478
 
0.7%
9896045
12.2%
97.54996
 
0.6%
9790633
11.5%
96.54043
 
0.5%

Temp
Real number (ℝ≥0)

MISSING

Distinct597
Distinct (%)0.2%
Missing523314
Missing (%)66.2%
Infinite0
Infinite (%)0.0%
Mean37.02673699
Minimum20.9
Maximum42.22
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.0 MiB
2021-11-29T19:21:12.000128image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum20.9
5-th percentile35.78
Q136.56
median37.06
Q337.55
95-th percentile38.22
Maximum42.22
Range21.32
Interquartile range (IQR)0.99

Descriptive statistics

Standard deviation0.7803170183
Coefficient of variation (CV)0.02107442032
Kurtosis4.554271772
Mean37.02673699
Median Absolute Deviation (MAD)0.5
Skewness-0.4334477302
Sum9882473.13
Variance0.6088946491
MonotonicityNot monotonic
2021-11-29T19:21:12.259822image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3711252
 
1.4%
37.58618
 
1.1%
36.677403
 
0.9%
36.897061
 
0.9%
37.45882
 
0.7%
37.175740
 
0.7%
37.35695
 
0.7%
37.65678
 
0.7%
36.565598
 
0.7%
36.55417
 
0.7%
Other values (587)198557
 
25.1%
(Missing)523314
66.2%
ValueCountFrequency (%)
20.91
 
< 0.1%
211
 
< 0.1%
231
 
< 0.1%
23.61
 
< 0.1%
26.61
 
< 0.1%
26.675
< 0.1%
27.91
 
< 0.1%
281
 
< 0.1%
29.61
 
< 0.1%
29.611
 
< 0.1%
ValueCountFrequency (%)
42.221
< 0.1%
41.971
< 0.1%
41.921
< 0.1%
41.711
< 0.1%
41.642
< 0.1%
41.61
< 0.1%
41.541
< 0.1%
41.442
< 0.1%
41.311
< 0.1%
41.221
< 0.1%

SBP
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct762
Distinct (%)0.1%
Missing120201
Missing (%)15.2%
Infinite0
Infinite (%)0.0%
Mean120.9623595
Minimum22
Maximum281
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.0 MiB
2021-11-29T19:21:12.514924image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum22
5-th percentile91
Q1105
median118.5
Q3134
95-th percentile160
Maximum281
Range259
Interquartile range (IQR)29

Descriptive statistics

Standard deviation21.52056743
Coefficient of variation (CV)0.1779112736
Kurtosis0.3503594755
Mean120.9623595
Median Absolute Deviation (MAD)14.5
Skewness0.5511779107
Sum81046474.31
Variance463.1348226
MonotonicityNot monotonic
2021-11-29T19:21:12.785011image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11012042
 
1.5%
11211907
 
1.5%
11411790
 
1.5%
11311656
 
1.5%
11611518
 
1.5%
11111485
 
1.5%
11511463
 
1.5%
10911458
 
1.4%
12011381
 
1.4%
10811380
 
1.4%
Other values (752)553934
70.1%
(Missing)120201
 
15.2%
ValueCountFrequency (%)
221
< 0.1%
23.51
< 0.1%
241
< 0.1%
251
< 0.1%
262
< 0.1%
271
< 0.1%
27.51
< 0.1%
282
< 0.1%
292
< 0.1%
301
< 0.1%
ValueCountFrequency (%)
2811
< 0.1%
2741
< 0.1%
272.51
< 0.1%
2721
< 0.1%
2501
< 0.1%
2471
< 0.1%
2461
< 0.1%
2452
< 0.1%
2421
< 0.1%
2411
< 0.1%

MAP
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct915
Distinct (%)0.1%
Missing80858
Missing (%)10.2%
Infinite0
Infinite (%)0.0%
Mean78.76734527
Minimum20
Maximum300
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.0 MiB
2021-11-29T19:21:13.056804image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum20
5-th percentile58
Q168
median77
Q387.33
95-th percentile105
Maximum300
Range280
Interquartile range (IQR)19.33

Descriptive statistics

Standard deviation15.044038
Coefficient of variation (CV)0.1909933355
Kurtosis6.753156317
Mean78.76734527
Median Absolute Deviation (MAD)9.17
Skewness1.127452271
Sum55874167.74
Variance226.3230794
MonotonicityNot monotonic
2021-11-29T19:21:13.313125image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7216577
 
2.1%
7316395
 
2.1%
7516170
 
2.0%
7416085
 
2.0%
7116000
 
2.0%
7015852
 
2.0%
7615808
 
2.0%
7815573
 
2.0%
6915561
 
2.0%
7715519
 
2.0%
Other values (905)549817
69.6%
(Missing)80858
 
10.2%
ValueCountFrequency (%)
2020
< 0.1%
20.331
 
< 0.1%
20.52
 
< 0.1%
2111
< 0.1%
21.332
 
< 0.1%
21.51
 
< 0.1%
2220
< 0.1%
22.53
 
< 0.1%
2314
< 0.1%
23.331
 
< 0.1%
ValueCountFrequency (%)
3002
< 0.1%
2983
< 0.1%
2972
< 0.1%
2954
< 0.1%
2943
< 0.1%
2933
< 0.1%
2921
 
< 0.1%
2912
< 0.1%
2902
< 0.1%
2891
 
< 0.1%

DBP
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct398
Distinct (%)0.1%
Missing380297
Missing (%)48.1%
Infinite0
Infinite (%)0.0%
Mean59.98580936
Minimum20
Maximum298
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.0 MiB
2021-11-29T19:21:13.575624image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum20
5-th percentile42.5
Q151
median58.5
Q367
95-th percentile82
Maximum298
Range278
Interquartile range (IQR)16

Descriptive statistics

Standard deviation12.57277085
Coefficient of variation (CV)0.2095957525
Kurtosis4.520557717
Mean59.98580936
Median Absolute Deviation (MAD)7.5
Skewness1.04032984
Sum24589263
Variance158.0745668
MonotonicityNot monotonic
2021-11-29T19:21:13.831141image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5513565
 
1.7%
5613440
 
1.7%
5313400
 
1.7%
5413392
 
1.7%
5713209
 
1.7%
5813006
 
1.6%
5212829
 
1.6%
5912755
 
1.6%
6012590
 
1.6%
6111963
 
1.5%
Other values (388)279769
35.4%
(Missing)380297
48.1%
ValueCountFrequency (%)
2018
< 0.1%
20.53
 
< 0.1%
2114
< 0.1%
21.51
 
< 0.1%
2221
< 0.1%
22.53
 
< 0.1%
2333
< 0.1%
23.251
 
< 0.1%
23.52
 
< 0.1%
2426
< 0.1%
ValueCountFrequency (%)
2981
< 0.1%
2871
< 0.1%
2721
< 0.1%
2691
< 0.1%
2681
< 0.1%
2671
< 0.1%
2461
< 0.1%
2321
< 0.1%
2221
< 0.1%
2211
< 0.1%

Resp
Real number (ℝ≥0)

MISSING

Distinct199
Distinct (%)< 0.1%
Missing77258
Missing (%)9.8%
Infinite0
Infinite (%)0.0%
Mean18.77345951
Minimum1
Maximum69
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.0 MiB
2021-11-29T19:21:14.102051image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile11
Q115
median18
Q322
95-th percentile28
Maximum69
Range68
Interquartile range (IQR)7

Descriptive statistics

Standard deviation5.395749814
Coefficient of variation (CV)0.2874137189
Kurtosis1.934108904
Mean18.77345951
Median Absolute Deviation (MAD)3
Skewness0.8725668118
Sum13384669.37
Variance29.11411605
MonotonicityNot monotonic
2021-11-29T19:21:14.548867image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1659163
 
7.5%
1857179
 
7.2%
2050926
 
6.4%
1449161
 
6.2%
1747936
 
6.1%
1945006
 
5.7%
1542786
 
5.4%
2137284
 
4.7%
2235984
 
4.6%
1232012
 
4.1%
Other values (189)255520
32.3%
(Missing)77258
 
9.8%
ValueCountFrequency (%)
119
 
< 0.1%
252
 
< 0.1%
2.51
 
< 0.1%
3109
< 0.1%
3.54
 
< 0.1%
3.841
 
< 0.1%
4166
< 0.1%
4.53
 
< 0.1%
5247
< 0.1%
5.251
 
< 0.1%
ValueCountFrequency (%)
693
 
< 0.1%
677
< 0.1%
662
 
< 0.1%
65.51
 
< 0.1%
656
< 0.1%
646
< 0.1%
636
< 0.1%
623
 
< 0.1%
614
 
< 0.1%
6014
< 0.1%

EtCO2
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing790215
Missing (%)100.0%
Memory size6.0 MiB

BaseExcess
Real number (ℝ)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING
ZEROS

Distinct110
Distinct (%)0.1%
Missing707834
Missing (%)89.6%
Infinite0
Infinite (%)0.0%
Mean-0.6475370534
Minimum-32
Maximum100
Zeros19355
Zeros (%)2.4%
Negative37745
Negative (%)4.8%
Memory size6.0 MiB
2021-11-29T19:21:14.817216image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum-32
5-th percentile-7
Q1-3
median0
Q31
95-th percentile6
Maximum100
Range132
Interquartile range (IQR)4

Descriptive statistics

Standard deviation4.286641188
Coefficient of variation (CV)-6.619916443
Kurtosis7.696001434
Mean-0.6475370534
Median Absolute Deviation (MAD)2
Skewness0.008423884272
Sum-53344.75
Variance18.37529267
MonotonicityNot monotonic
2021-11-29T19:21:15.093968image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
019355
 
2.4%
-17859
 
1.0%
-26937
 
0.9%
16100
 
0.8%
-35934
 
0.8%
24863
 
0.6%
-44519
 
0.6%
33959
 
0.5%
-53347
 
0.4%
42847
 
0.4%
Other values (100)16661
 
2.1%
(Missing)707834
89.6%
ValueCountFrequency (%)
-321
 
< 0.1%
-301
 
< 0.1%
-292
 
< 0.1%
-285
< 0.1%
-275
< 0.1%
-26.52
 
< 0.1%
-265
< 0.1%
-25.51
 
< 0.1%
-2511
< 0.1%
-24.51
 
< 0.1%
ValueCountFrequency (%)
1001
 
< 0.1%
49.51
 
< 0.1%
441
 
< 0.1%
361
 
< 0.1%
281
 
< 0.1%
263
 
< 0.1%
252
 
< 0.1%
248
< 0.1%
234
 
< 0.1%
2210
< 0.1%

HCO3
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct74
Distinct (%)0.1%
Missing726598
Missing (%)91.9%
Infinite0
Infinite (%)0.0%
Mean24.09447553
Minimum0
Maximum55
Zeros2
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size6.0 MiB
2021-11-29T19:21:15.369822image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile17
Q122
median24
Q327
95-th percentile31
Maximum55
Range55
Interquartile range (IQR)5

Descriptive statistics

Standard deviation4.39619219
Coefficient of variation (CV)0.1824564383
Kurtosis2.118839042
Mean24.09447553
Median Absolute Deviation (MAD)2
Skewness0.1518748194
Sum1532818.25
Variance19.32650577
MonotonicityNot monotonic
2021-11-29T19:21:15.626107image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
247092
 
0.9%
256978
 
0.9%
236670
 
0.8%
265978
 
0.8%
225536
 
0.7%
274734
 
0.6%
214161
 
0.5%
283418
 
0.4%
203253
 
0.4%
292473
 
0.3%
Other values (64)13324
 
1.7%
(Missing)726598
91.9%
ValueCountFrequency (%)
02
 
< 0.1%
513
 
< 0.1%
622
 
< 0.1%
730
 
< 0.1%
7.51
 
< 0.1%
856
< 0.1%
8.51
 
< 0.1%
958
< 0.1%
1095
< 0.1%
10.51
 
< 0.1%
ValueCountFrequency (%)
552
 
< 0.1%
531
 
< 0.1%
521
 
< 0.1%
504
 
< 0.1%
496
 
< 0.1%
483
 
< 0.1%
479
 
< 0.1%
4610
 
< 0.1%
4516
< 0.1%
4425
< 0.1%

FiO2
Real number (ℝ≥0)

MISSING

Distinct92
Distinct (%)0.1%
Missing678060
Missing (%)85.8%
Infinite0
Infinite (%)0.0%
Mean0.5262479604
Minimum0
Maximum10
Zeros81
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size6.0 MiB
2021-11-29T19:21:15.898793image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.35
Q10.4
median0.5
Q30.55
95-th percentile1
Maximum10
Range10
Interquartile range (IQR)0.15

Descriptive statistics

Standard deviation0.1858691243
Coefficient of variation (CV)0.3531968546
Kurtosis74.55575063
Mean0.5262479604
Median Absolute Deviation (MAD)0.1
Skewness2.952150174
Sum59021.34
Variance0.03454733139
MonotonicityNot monotonic
2021-11-29T19:21:16.163302image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.439334
 
5.0%
0.536666
 
4.6%
19439
 
1.2%
0.68346
 
1.1%
0.75543
 
0.7%
0.353342
 
0.4%
0.82344
 
0.3%
0.32309
 
0.3%
0.45967
 
0.1%
0.95599
 
0.1%
Other values (82)3266
 
0.4%
(Missing)678060
85.8%
ValueCountFrequency (%)
081
< 0.1%
0.0247
< 0.1%
0.0329
 
< 0.1%
0.0470
< 0.1%
0.0522
 
< 0.1%
0.065
 
< 0.1%
0.083
 
< 0.1%
0.13
 
< 0.1%
0.112
 
< 0.1%
0.122
 
< 0.1%
ValueCountFrequency (%)
101
 
< 0.1%
71
 
< 0.1%
19439
1.2%
0.9922
 
< 0.1%
0.9836
 
< 0.1%
0.9711
 
< 0.1%
0.9622
 
< 0.1%
0.95599
 
0.1%
0.949
 
< 0.1%
0.9312
 
< 0.1%

pH
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct99
Distinct (%)0.1%
Missing699600
Missing (%)88.5%
Infinite0
Infinite (%)0.0%
Mean7.380242785
Minimum6.62
Maximum7.93
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.0 MiB
2021-11-29T19:21:16.415441image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum6.62
5-th percentile7.26
Q17.34
median7.39
Q37.43
95-th percentile7.48
Maximum7.93
Range1.31
Interquartile range (IQR)0.09

Descriptive statistics

Standard deviation0.07187695908
Coefficient of variation (CV)0.009739104955
Kurtosis3.639116816
Mean7.380242785
Median Absolute Deviation (MAD)0.04
Skewness-0.9050323186
Sum668760.7
Variance0.005166297247
MonotonicityNot monotonic
2021-11-29T19:21:16.696623image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7.45830
 
0.7%
7.385779
 
0.7%
7.395620
 
0.7%
7.415406
 
0.7%
7.375314
 
0.7%
7.425235
 
0.7%
7.365168
 
0.7%
7.354591
 
0.6%
7.434565
 
0.6%
7.444176
 
0.5%
Other values (89)38931
 
4.9%
(Missing)699600
88.5%
ValueCountFrequency (%)
6.621
 
< 0.1%
6.631
 
< 0.1%
6.651
 
< 0.1%
6.781
 
< 0.1%
6.792
 
< 0.1%
6.81
 
< 0.1%
6.811
 
< 0.1%
6.823
< 0.1%
6.853
< 0.1%
6.866
< 0.1%
ValueCountFrequency (%)
7.931
 
< 0.1%
7.81
 
< 0.1%
7.781
 
< 0.1%
7.731
 
< 0.1%
7.721
 
< 0.1%
7.711
 
< 0.1%
7.692
 
< 0.1%
7.682
 
< 0.1%
7.672
 
< 0.1%
7.666
< 0.1%

PaCO2
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct158
Distinct (%)0.2%
Missing720927
Missing (%)91.2%
Infinite0
Infinite (%)0.0%
Mean41.1661471
Minimum10
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.0 MiB
2021-11-29T19:21:16.977949image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile29
Q136
median40
Q345
95-th percentile57
Maximum100
Range90
Interquartile range (IQR)9

Descriptive statistics

Standard deviation8.996603913
Coefficient of variation (CV)0.218543744
Kurtosis5.119448816
Mean41.1661471
Median Absolute Deviation (MAD)5
Skewness1.46888074
Sum2852320
Variance80.93888196
MonotonicityNot monotonic
2021-11-29T19:21:17.240715image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
403998
 
0.5%
383973
 
0.5%
393905
 
0.5%
423858
 
0.5%
373723
 
0.5%
413723
 
0.5%
363534
 
0.4%
433217
 
0.4%
443049
 
0.4%
352980
 
0.4%
Other values (148)33328
 
4.2%
(Missing)720927
91.2%
ValueCountFrequency (%)
101
 
< 0.1%
113
 
< 0.1%
122
 
< 0.1%
133
 
< 0.1%
145
 
< 0.1%
156
 
< 0.1%
1615
< 0.1%
16.51
 
< 0.1%
1716
< 0.1%
1826
< 0.1%
ValueCountFrequency (%)
10012
< 0.1%
999
< 0.1%
986
 
< 0.1%
97.51
 
< 0.1%
9711
< 0.1%
965
 
< 0.1%
95.51
 
< 0.1%
957
 
< 0.1%
94.51
 
< 0.1%
9418
< 0.1%

SaO2
Real number (ℝ≥0)

MISSING

Distinct140
Distinct (%)0.4%
Missing751055
Missing (%)95.0%
Infinite0
Infinite (%)0.0%
Mean91.21545582
Minimum24
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.0 MiB
2021-11-29T19:21:17.510568image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum24
5-th percentile62
Q193
median97
Q398
95-th percentile99
Maximum100
Range76
Interquartile range (IQR)5

Descriptive statistics

Standard deviation12.22622975
Coefficient of variation (CV)0.1340368213
Kurtosis2.799561703
Mean91.21545582
Median Absolute Deviation (MAD)1
Skewness-1.955553505
Sum3571997.25
Variance149.4806939
MonotonicityNot monotonic
2021-11-29T19:21:17.785995image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
9810820
 
1.4%
976853
 
0.9%
963870
 
0.5%
993264
 
0.4%
952169
 
0.3%
941430
 
0.2%
93801
 
0.1%
92479
 
0.1%
91329
 
< 0.1%
67296
 
< 0.1%
Other values (130)8849
 
1.1%
(Missing)751055
95.0%
ValueCountFrequency (%)
241
 
< 0.1%
261
 
< 0.1%
272
 
< 0.1%
282
 
< 0.1%
293
< 0.1%
305
< 0.1%
311
 
< 0.1%
322
 
< 0.1%
331
 
< 0.1%
33.51
 
< 0.1%
ValueCountFrequency (%)
100284
 
< 0.1%
99.55
 
< 0.1%
99.31
 
< 0.1%
993264
 
0.4%
98.81
 
< 0.1%
98.5100
 
< 0.1%
9810820
1.4%
97.752
 
< 0.1%
97.5124
 
< 0.1%
976853
0.9%

AST
Real number (ℝ≥0)

MISSING

Distinct1523
Distinct (%)12.9%
Missing778395
Missing (%)98.5%
Infinite0
Infinite (%)0.0%
Mean356.2075296
Minimum3
Maximum9890
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.0 MiB
2021-11-29T19:21:18.257892image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile15
Q128
median57
Q3180
95-th percentile1728.15
Maximum9890
Range9887
Interquartile range (IQR)152

Descriptive statistics

Standard deviation1025.654672
Coefficient of variation (CV)2.879373923
Kurtosis32.52747342
Mean356.2075296
Median Absolute Deviation (MAD)37
Skewness5.339066647
Sum4210373
Variance1051967.506
MonotonicityNot monotonic
2021-11-29T19:21:18.526652image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
17214
 
< 0.1%
19211
 
< 0.1%
18211
 
< 0.1%
24195
 
< 0.1%
21188
 
< 0.1%
20184
 
< 0.1%
16178
 
< 0.1%
23177
 
< 0.1%
22176
 
< 0.1%
26168
 
< 0.1%
Other values (1513)9918
 
1.3%
(Missing)778395
98.5%
ValueCountFrequency (%)
32
 
< 0.1%
41
 
< 0.1%
52
 
< 0.1%
5.51
 
< 0.1%
66
 
< 0.1%
79
 
< 0.1%
821
 
< 0.1%
930
< 0.1%
1057
< 0.1%
1173
< 0.1%
ValueCountFrequency (%)
98901
< 0.1%
98402
< 0.1%
97301
< 0.1%
96401
< 0.1%
95071
< 0.1%
94951
< 0.1%
94901
< 0.1%
94561
< 0.1%
94301
< 0.1%
92481
< 0.1%

BUN
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct214
Distinct (%)0.3%
Missing725739
Missing (%)91.8%
Infinite0
Infinite (%)0.0%
Mean24.34670885
Minimum1
Maximum266
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.0 MiB
2021-11-29T19:21:18.784822image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile7
Q112
median18
Q329
95-th percentile66
Maximum266
Range265
Interquartile range (IQR)17

Descriptive statistics

Standard deviation20.15443688
Coefficient of variation (CV)0.8278094999
Kurtosis8.287486768
Mean24.34670885
Median Absolute Deviation (MAD)7
Skewness2.455079417
Sum1569778.4
Variance406.201326
MonotonicityNot monotonic
2021-11-29T19:21:19.061327image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
143163
 
0.4%
123063
 
0.4%
133052
 
0.4%
153028
 
0.4%
112905
 
0.4%
162704
 
0.3%
102695
 
0.3%
172595
 
0.3%
92343
 
0.3%
182285
 
0.3%
Other values (204)36643
 
4.6%
(Missing)725739
91.8%
ValueCountFrequency (%)
122
 
< 0.1%
288
 
< 0.1%
2.51
 
< 0.1%
3272
 
< 0.1%
4443
 
0.1%
5782
 
0.1%
61151
0.1%
71582
0.2%
81966
0.2%
8.51
 
< 0.1%
ValueCountFrequency (%)
2661
 
< 0.1%
2351
 
< 0.1%
2341
 
< 0.1%
2321
 
< 0.1%
2051
 
< 0.1%
2011
 
< 0.1%
1951
 
< 0.1%
1851
 
< 0.1%
1844
< 0.1%
1811
 
< 0.1%

Alkalinephos
Real number (ℝ≥0)

MISSING

Distinct611
Distinct (%)5.3%
Missing778683
Missing (%)98.5%
Infinite0
Infinite (%)0.0%
Mean114.2033039
Minimum7
Maximum3833
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.0 MiB
2021-11-29T19:21:19.336277image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum7
5-th percentile37
Q156
median78
Q3119
95-th percentile300
Maximum3833
Range3826
Interquartile range (IQR)63

Descriptive statistics

Standard deviation147.3628021
Coefficient of variation (CV)1.290354982
Kurtosis173.8797785
Mean114.2033039
Median Absolute Deviation (MAD)27
Skewness10.01689255
Sum1316992.5
Variance21715.79543
MonotonicityNot monotonic
2021-11-29T19:21:19.607653image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
55166
 
< 0.1%
49163
 
< 0.1%
50151
 
< 0.1%
52150
 
< 0.1%
58150
 
< 0.1%
53148
 
< 0.1%
54145
 
< 0.1%
69143
 
< 0.1%
59142
 
< 0.1%
47140
 
< 0.1%
Other values (601)10034
 
1.3%
(Missing)778683
98.5%
ValueCountFrequency (%)
72
 
< 0.1%
112
 
< 0.1%
121
 
< 0.1%
131
 
< 0.1%
142
 
< 0.1%
152
 
< 0.1%
161
 
< 0.1%
172
 
< 0.1%
186
< 0.1%
192
 
< 0.1%
ValueCountFrequency (%)
38332
< 0.1%
36192
< 0.1%
25281
< 0.1%
24401
< 0.1%
23321
< 0.1%
21901
< 0.1%
21212
< 0.1%
21011
< 0.1%
19192
< 0.1%
17991
< 0.1%

Calcium
Real number (ℝ≥0)

MISSING

Distinct135
Distinct (%)0.3%
Missing750897
Missing (%)95.0%
Infinite0
Infinite (%)0.0%
Mean8.316976957
Minimum1.6
Maximum22
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.0 MiB
2021-11-29T19:21:19.895551image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1.6
5-th percentile7.1
Q17.8
median8.3
Q38.8
95-th percentile9.5
Maximum22
Range20.4
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.8193044817
Coefficient of variation (CV)0.09850988958
Kurtosis11.94484061
Mean8.316976957
Median Absolute Deviation (MAD)0.5
Skewness1.114800945
Sum327006.9
Variance0.6712598337
MonotonicityNot monotonic
2021-11-29T19:21:20.163121image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8.42389
 
0.3%
8.32365
 
0.3%
8.22261
 
0.3%
8.52250
 
0.3%
8.12249
 
0.3%
8.62085
 
0.3%
82055
 
0.3%
7.91885
 
0.2%
8.71850
 
0.2%
7.81697
 
0.2%
Other values (125)18232
 
2.3%
(Missing)750897
95.0%
ValueCountFrequency (%)
1.61
 
< 0.1%
2.82
< 0.1%
3.51
 
< 0.1%
3.61
 
< 0.1%
3.71
 
< 0.1%
3.91
 
< 0.1%
4.21
 
< 0.1%
4.33
< 0.1%
4.42
< 0.1%
4.53
< 0.1%
ValueCountFrequency (%)
221
< 0.1%
21.51
< 0.1%
19.61
< 0.1%
19.21
< 0.1%
18.41
< 0.1%
17.51
< 0.1%
171
< 0.1%
16.61
< 0.1%
16.21
< 0.1%
15.71
< 0.1%

Chloride
Real number (ℝ≥0)

MISSING

Distinct99
Distinct (%)0.2%
Missing724438
Missing (%)91.7%
Infinite0
Infinite (%)0.0%
Mean105.7650623
Minimum26
Maximum145
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.0 MiB
2021-11-29T19:21:20.435884image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum26
5-th percentile96
Q1102
median106
Q3109
95-th percentile115
Maximum145
Range119
Interquartile range (IQR)7

Descriptive statistics

Standard deviation5.939929059
Coefficient of variation (CV)0.05616154269
Kurtosis2.685617615
Mean105.7650623
Median Absolute Deviation (MAD)3
Skewness-0.1311256904
Sum6956908.5
Variance35.28275723
MonotonicityNot monotonic
2021-11-29T19:21:20.712662image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1065208
 
0.7%
1075060
 
0.6%
1054928
 
0.6%
1084707
 
0.6%
1044586
 
0.6%
1094358
 
0.6%
1034043
 
0.5%
1103532
 
0.4%
1023438
 
0.4%
1112988
 
0.4%
Other values (89)22929
 
2.9%
(Missing)724438
91.7%
ValueCountFrequency (%)
261
 
< 0.1%
381
 
< 0.1%
631
 
< 0.1%
662
< 0.1%
671
 
< 0.1%
691
 
< 0.1%
703
< 0.1%
732
< 0.1%
744
< 0.1%
753
< 0.1%
ValueCountFrequency (%)
1451
 
< 0.1%
1411
 
< 0.1%
1403
 
< 0.1%
13910
< 0.1%
1386
< 0.1%
13711
< 0.1%
1367
< 0.1%
13510
< 0.1%
1343
 
< 0.1%
1337
< 0.1%

Creatinine
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct178
Distinct (%)0.3%
Missing737728
Missing (%)93.4%
Infinite0
Infinite (%)0.0%
Mean1.404382037
Minimum0.1
Maximum46.6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.0 MiB
2021-11-29T19:21:20.977766image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0.1
5-th percentile0.5
Q10.7
median0.9
Q31.4
95-th percentile4.4
Maximum46.6
Range46.5
Interquartile range (IQR)0.7

Descriptive statistics

Standard deviation1.527545493
Coefficient of variation (CV)1.087699395
Kurtosis36.55568778
Mean1.404382037
Median Absolute Deviation (MAD)0.3
Skewness4.334273262
Sum73711.8
Variance2.333395232
MonotonicityNot monotonic
2021-11-29T19:21:21.240897image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.76211
 
0.8%
0.86021
 
0.8%
0.65150
 
0.7%
0.95064
 
0.6%
13855
 
0.5%
0.53530
 
0.4%
1.12935
 
0.4%
1.22244
 
0.3%
1.31802
 
0.2%
0.41524
 
0.2%
Other values (168)14151
 
1.8%
(Missing)737728
93.4%
ValueCountFrequency (%)
0.130
 
< 0.1%
0.2109
 
< 0.1%
0.3438
 
0.1%
0.41524
 
0.2%
0.53530
0.4%
0.552
 
< 0.1%
0.65150
0.7%
0.651
 
< 0.1%
0.76211
0.8%
0.752
 
< 0.1%
ValueCountFrequency (%)
46.61
< 0.1%
29.11
< 0.1%
281
< 0.1%
25.11
< 0.1%
21.41
< 0.1%
19.91
< 0.1%
18.81
< 0.1%
18.51
< 0.1%
17.61
< 0.1%
17.31
< 0.1%

Bilirubin_direct
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct139
Distinct (%)11.8%
Missing789033
Missing (%)99.9%
Infinite0
Infinite (%)0.0%
Mean3.114213198
Minimum0.1
Maximum37.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.0 MiB
2021-11-29T19:21:21.504238image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0.1
5-th percentile0.2
Q10.5
median1.4
Q33.7
95-th percentile12
Maximum37.5
Range37.4
Interquartile range (IQR)3.2

Descriptive statistics

Standard deviation4.631446576
Coefficient of variation (CV)1.487196374
Kurtosis12.20225941
Mean3.114213198
Median Absolute Deviation (MAD)1.1
Skewness3.149536649
Sum3681
Variance21.45029739
MonotonicityNot monotonic
2021-11-29T19:21:21.760499image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.275
 
< 0.1%
0.468
 
< 0.1%
0.356
 
< 0.1%
0.156
 
< 0.1%
0.555
 
< 0.1%
0.745
 
< 0.1%
0.642
 
< 0.1%
0.841
 
< 0.1%
138
 
< 0.1%
0.934
 
< 0.1%
Other values (129)672
 
0.1%
(Missing)789033
99.9%
ValueCountFrequency (%)
0.156
< 0.1%
0.275
< 0.1%
0.356
< 0.1%
0.468
< 0.1%
0.555
< 0.1%
0.642
< 0.1%
0.745
< 0.1%
0.841
< 0.1%
0.934
< 0.1%
138
< 0.1%
ValueCountFrequency (%)
37.51
< 0.1%
351
< 0.1%
301
< 0.1%
29.12
< 0.1%
282
< 0.1%
26.41
< 0.1%
25.21
< 0.1%
22.82
< 0.1%
22.52
< 0.1%
22.21
< 0.1%

Glucose
Real number (ℝ≥0)

MISSING

Distinct864
Distinct (%)0.9%
Missing693559
Missing (%)87.8%
Infinite0
Infinite (%)0.0%
Mean133.6092206
Minimum10
Maximum988
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.0 MiB
2021-11-29T19:21:22.240246image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile79
Q1104
median124
Q3150
95-th percentile218
Maximum988
Range978
Interquartile range (IQR)46

Descriptive statistics

Standard deviation51.58358027
Coefficient of variation (CV)0.3860779969
Kurtosis31.10214074
Mean133.6092206
Median Absolute Deviation (MAD)22
Skewness3.692394293
Sum12914132.83
Variance2660.865753
MonotonicityNot monotonic
2021-11-29T19:21:22.513015image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1181329
 
0.2%
1141216
 
0.2%
1081210
 
0.2%
1161203
 
0.2%
1211199
 
0.2%
1191199
 
0.2%
1131194
 
0.2%
1121188
 
0.2%
1111185
 
0.1%
1171182
 
0.1%
Other values (854)84551
 
10.7%
(Missing)693559
87.8%
ValueCountFrequency (%)
101
 
< 0.1%
111
 
< 0.1%
141
 
< 0.1%
171
 
< 0.1%
181
 
< 0.1%
192
< 0.1%
212
< 0.1%
221
 
< 0.1%
242
< 0.1%
253
< 0.1%
ValueCountFrequency (%)
9881
< 0.1%
9601
< 0.1%
9521
< 0.1%
9421
< 0.1%
9341
< 0.1%
9291
< 0.1%
9241
< 0.1%
9211
< 0.1%
9141
< 0.1%
9131
< 0.1%

Lactate
Real number (ℝ≥0)

MISSING

Distinct351
Distinct (%)1.3%
Missing763072
Missing (%)96.6%
Infinite0
Infinite (%)0.0%
Mean2.469202741
Minimum0.2
Maximum31
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.0 MiB
2021-11-29T19:21:22.778575image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0.2
5-th percentile0.8
Q11.2
median1.8
Q32.8
95-th percentile6.4
Maximum31
Range30.8
Interquartile range (IQR)1.6

Descriptive statistics

Standard deviation2.32900126
Coefficient of variation (CV)0.9432199396
Kurtosis22.79142022
Mean2.469202741
Median Absolute Deviation (MAD)0.7
Skewness3.937763604
Sum67021.57
Variance5.42424687
MonotonicityNot monotonic
2021-11-29T19:21:23.042592image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.21412
 
0.2%
11390
 
0.2%
1.31356
 
0.2%
1.41344
 
0.2%
1.11321
 
0.2%
0.91195
 
0.2%
1.51154
 
0.1%
1.61142
 
0.1%
1.71048
 
0.1%
1.8973
 
0.1%
Other values (341)14808
 
1.9%
(Missing)763072
96.6%
ValueCountFrequency (%)
0.21
 
< 0.1%
0.313
 
< 0.1%
0.371
 
< 0.1%
0.433
 
< 0.1%
0.569
 
< 0.1%
0.552
 
< 0.1%
0.6277
< 0.1%
0.653
 
< 0.1%
0.7534
0.1%
0.731
 
< 0.1%
ValueCountFrequency (%)
311
< 0.1%
28.91
< 0.1%
28.81
< 0.1%
271
< 0.1%
26.92
< 0.1%
26.71
< 0.1%
26.61
< 0.1%
261
< 0.1%
25.91
< 0.1%
25.81
< 0.1%

Magnesium
Real number (ℝ≥0)

MISSING

Distinct86
Distinct (%)0.1%
Missing728734
Missing (%)92.2%
Infinite0
Infinite (%)0.0%
Mean2.041003725
Minimum0.2
Maximum9.7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.0 MiB
2021-11-29T19:21:23.323617image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0.2
5-th percentile1.5
Q11.8
median2
Q32.2
95-th percentile2.7
Maximum9.7
Range9.5
Interquartile range (IQR)0.4

Descriptive statistics

Standard deviation0.3900279372
Coefficient of variation (CV)0.1910961418
Kurtosis18.673673
Mean2.041003725
Median Absolute Deviation (MAD)0.2
Skewness1.8992782
Sum125482.95
Variance0.1521217918
MonotonicityNot monotonic
2021-11-29T19:21:23.595370image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
27834
 
1.0%
1.97463
 
0.9%
2.17304
 
0.9%
1.86511
 
0.8%
2.25783
 
0.7%
1.74746
 
0.6%
2.34397
 
0.6%
1.63207
 
0.4%
2.43154
 
0.4%
2.52103
 
0.3%
Other values (76)8979
 
1.1%
(Missing)728734
92.2%
ValueCountFrequency (%)
0.21
 
< 0.1%
0.76
 
< 0.1%
0.88
 
< 0.1%
0.927
 
< 0.1%
191
 
< 0.1%
1.1161
 
< 0.1%
1.141
 
< 0.1%
1.2336
< 0.1%
1.251
 
< 0.1%
1.3602
0.1%
ValueCountFrequency (%)
9.71
 
< 0.1%
9.61
 
< 0.1%
8.92
 
< 0.1%
8.31
 
< 0.1%
8.21
 
< 0.1%
7.61
 
< 0.1%
7.51
 
< 0.1%
7.31
 
< 0.1%
6.71
 
< 0.1%
6.55
< 0.1%

Phosphate
Real number (ℝ≥0)

HIGH CORRELATION
MISSING

Distinct162
Distinct (%)0.4%
Missing750319
Missing (%)95.0%
Infinite0
Infinite (%)0.0%
Mean3.588572789
Minimum0.2
Maximum18.8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.0 MiB
2021-11-29T19:21:23.863736image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0.2
5-th percentile1.8
Q12.7
median3.4
Q34.2
95-th percentile6.2
Maximum18.8
Range18.6
Interquartile range (IQR)1.5

Descriptive statistics

Standard deviation1.445631953
Coefficient of variation (CV)0.4028431463
Kurtosis6.270038963
Mean3.588572789
Median Absolute Deviation (MAD)0.7
Skewness1.729356705
Sum143169.7
Variance2.089851744
MonotonicityNot monotonic
2021-11-29T19:21:24.126214image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3.11555
 
0.2%
3.21542
 
0.2%
2.91512
 
0.2%
3.41476
 
0.2%
3.31475
 
0.2%
31452
 
0.2%
2.81416
 
0.2%
3.51376
 
0.2%
2.71376
 
0.2%
3.61345
 
0.2%
Other values (152)25371
 
3.2%
(Missing)750319
95.0%
ValueCountFrequency (%)
0.21
 
< 0.1%
0.35
 
< 0.1%
0.45
 
< 0.1%
0.521
 
< 0.1%
0.617
 
< 0.1%
0.739
< 0.1%
0.838
< 0.1%
0.940
< 0.1%
178
< 0.1%
1.194
< 0.1%
ValueCountFrequency (%)
18.81
< 0.1%
17.61
< 0.1%
16.91
< 0.1%
16.51
< 0.1%
16.41
< 0.1%
15.61
< 0.1%
151
< 0.1%
14.92
< 0.1%
14.71
< 0.1%
14.51
< 0.1%

Potassium
Real number (ℝ≥0)

MISSING

Distinct135
Distinct (%)0.2%
Missing704379
Missing (%)89.1%
Infinite0
Infinite (%)0.0%
Mean4.161507176
Minimum1
Maximum27.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.0 MiB
2021-11-29T19:21:24.404353image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.3
Q13.8
median4.1
Q34.5
95-th percentile5.2
Maximum27.5
Range26.5
Interquartile range (IQR)0.7

Descriptive statistics

Standard deviation0.6327191536
Coefficient of variation (CV)0.1520408657
Kurtosis26.46700796
Mean4.161507176
Median Absolute Deviation (MAD)0.4
Skewness1.753757537
Sum357207.13
Variance0.4003335273
MonotonicityNot monotonic
2021-11-29T19:21:24.685267image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
46737
 
0.9%
4.16498
 
0.8%
3.96358
 
0.8%
4.26269
 
0.8%
3.86044
 
0.8%
4.35619
 
0.7%
3.75065
 
0.6%
4.44839
 
0.6%
3.64278
 
0.5%
4.54133
 
0.5%
Other values (125)29996
 
3.8%
(Missing)704379
89.1%
ValueCountFrequency (%)
11
 
< 0.1%
1.51
 
< 0.1%
1.61
 
< 0.1%
1.84
 
< 0.1%
1.98
 
< 0.1%
24
 
< 0.1%
2.111
 
< 0.1%
2.28
 
< 0.1%
2.319
< 0.1%
2.430
< 0.1%
ValueCountFrequency (%)
27.51
 
< 0.1%
131
 
< 0.1%
104
< 0.1%
9.93
< 0.1%
9.83
< 0.1%
9.73
< 0.1%
9.53
< 0.1%
9.42
< 0.1%
9.31
 
< 0.1%
9.24
< 0.1%

Bilirubin_total
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct341
Distinct (%)3.5%
Missing780522
Missing (%)98.8%
Infinite0
Infinite (%)0.0%
Mean2.694403178
Minimum0.1
Maximum46.6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.0 MiB
2021-11-29T19:21:24.947134image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0.1
5-th percentile0.2
Q10.5
median0.9
Q32.2
95-th percentile11.6
Maximum46.6
Range46.5
Interquartile range (IQR)1.7

Descriptive statistics

Standard deviation5.242802476
Coefficient of variation (CV)1.945812163
Kurtosis21.70131202
Mean2.694403178
Median Absolute Deviation (MAD)0.5
Skewness4.275764467
Sum26116.85
Variance27.4869778
MonotonicityNot monotonic
2021-11-29T19:21:25.207215image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.4812
 
0.1%
0.5792
 
0.1%
0.3788
 
0.1%
0.6677
 
0.1%
0.7583
 
0.1%
0.8471
 
0.1%
0.2464
 
0.1%
0.9409
 
0.1%
1323
 
< 0.1%
1.1277
 
< 0.1%
Other values (331)4097
 
0.5%
(Missing)780522
98.8%
ValueCountFrequency (%)
0.199
 
< 0.1%
0.2464
0.1%
0.3788
0.1%
0.4812
0.1%
0.451
 
< 0.1%
0.5792
0.1%
0.6677
0.1%
0.7583
0.1%
0.8471
0.1%
0.9409
0.1%
ValueCountFrequency (%)
46.61
< 0.1%
46.51
< 0.1%
45.91
< 0.1%
44.92
< 0.1%
44.61
< 0.1%
44.31
< 0.1%
44.11
< 0.1%
43.71
< 0.1%
43.51
< 0.1%
43.21
< 0.1%

TroponinI
Real number (ℝ≥0)

MISSING

Distinct289
Distinct (%)29.9%
Missing789250
Missing (%)99.9%
Infinite0
Infinite (%)0.0%
Mean9.288186528
Minimum0.3
Maximum49.3
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.0 MiB
2021-11-29T19:21:25.461763image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0.3
5-th percentile0.4
Q11
median4.3
Q312.9
95-th percentile35.98
Maximum49.3
Range49
Interquartile range (IQR)11.9

Descriptive statistics

Standard deviation11.4128697
Coefficient of variation (CV)1.228751131
Kurtosis2.069654048
Mean9.288186528
Median Absolute Deviation (MAD)3.7
Skewness1.648824695
Sum8963.1
Variance130.2535947
MonotonicityNot monotonic
2021-11-29T19:21:25.731499image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.346
 
< 0.1%
0.439
 
< 0.1%
0.538
 
< 0.1%
0.837
 
< 0.1%
0.627
 
< 0.1%
0.726
 
< 0.1%
0.921
 
< 0.1%
120
 
< 0.1%
1.217
 
< 0.1%
1.614
 
< 0.1%
Other values (279)680
 
0.1%
(Missing)789250
99.9%
ValueCountFrequency (%)
0.346
< 0.1%
0.439
< 0.1%
0.538
< 0.1%
0.627
< 0.1%
0.726
< 0.1%
0.837
< 0.1%
0.921
< 0.1%
120
< 0.1%
1.112
 
< 0.1%
1.217
 
< 0.1%
ValueCountFrequency (%)
49.31
< 0.1%
491
< 0.1%
48.71
< 0.1%
48.52
< 0.1%
482
< 0.1%
47.51
< 0.1%
47.11
< 0.1%
46.51
< 0.1%
46.11
< 0.1%
461
< 0.1%

Hct
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct659
Distinct (%)0.7%
Missing697157
Missing (%)88.2%
Infinite0
Infinite (%)0.0%
Mean30.67489523
Minimum5.5
Maximum71.7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.0 MiB
2021-11-29T19:21:26.186521image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum5.5
5-th percentile23.5
Q127.4
median30.2
Q333.5
95-th percentile39.3
Maximum71.7
Range66.2
Interquartile range (IQR)6.1

Descriptive statistics

Standard deviation4.874651113
Coefficient of variation (CV)0.1589133745
Kurtosis1.080934426
Mean30.67489523
Median Absolute Deviation (MAD)3
Skewness0.5377661751
Sum2854544.4
Variance23.76222347
MonotonicityNot monotonic
2021-11-29T19:21:26.439990image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
291469
 
0.2%
321305
 
0.2%
301296
 
0.2%
281291
 
0.2%
311276
 
0.2%
261038
 
0.1%
271014
 
0.1%
331013
 
0.1%
34857
 
0.1%
29.4827
 
0.1%
Other values (649)81672
 
10.3%
(Missing)697157
88.2%
ValueCountFrequency (%)
5.51
< 0.1%
71
< 0.1%
8.81
< 0.1%
9.41
< 0.1%
9.71
< 0.1%
101
< 0.1%
10.32
< 0.1%
112
< 0.1%
11.51
< 0.1%
11.71
< 0.1%
ValueCountFrequency (%)
71.71
 
< 0.1%
69.71
 
< 0.1%
66.41
 
< 0.1%
66.22
< 0.1%
64.62
< 0.1%
61.82
< 0.1%
61.71
 
< 0.1%
611
 
< 0.1%
60.51
 
< 0.1%
60.34
< 0.1%

Hgb
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct297
Distinct (%)0.4%
Missing720394
Missing (%)91.2%
Infinite0
Infinite (%)0.0%
Mean10.58202804
Minimum2.2
Maximum32
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.0 MiB
2021-11-29T19:21:26.710925image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum2.2
5-th percentile8
Q19.4
median10.4
Q311.6
95-th percentile13.7
Maximum32
Range29.8
Interquartile range (IQR)2.2

Descriptive statistics

Standard deviation1.746026695
Coefficient of variation (CV)0.1649992504
Kurtosis0.9411009889
Mean10.58202804
Median Absolute Deviation (MAD)1.1
Skewness0.4753156
Sum738847.78
Variance3.048609218
MonotonicityNot monotonic
2021-11-29T19:21:26.967553image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
101811
 
0.2%
10.21756
 
0.2%
10.31753
 
0.2%
10.11732
 
0.2%
10.51676
 
0.2%
9.71670
 
0.2%
9.81658
 
0.2%
10.61648
 
0.2%
10.41638
 
0.2%
9.91606
 
0.2%
Other values (287)52873
 
6.7%
(Missing)720394
91.2%
ValueCountFrequency (%)
2.21
 
< 0.1%
3.11
 
< 0.1%
3.22
 
< 0.1%
3.32
 
< 0.1%
3.51
 
< 0.1%
41
 
< 0.1%
4.051
 
< 0.1%
4.15
< 0.1%
4.23
< 0.1%
4.34
< 0.1%
ValueCountFrequency (%)
321
 
< 0.1%
22.11
 
< 0.1%
21.81
 
< 0.1%
20.35
< 0.1%
19.61
 
< 0.1%
19.54
< 0.1%
19.41
 
< 0.1%
19.33
< 0.1%
19.21
 
< 0.1%
19.12
 
< 0.1%

PTT
Real number (ℝ≥0)

MISSING

Distinct1273
Distinct (%)3.3%
Missing751909
Missing (%)95.2%
Infinite0
Infinite (%)0.0%
Mean40.78193651
Minimum12.5
Maximum150
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.0 MiB
2021-11-29T19:21:27.228068image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum12.5
5-th percentile23.4
Q127.7
median32.4
Q342.9
95-th percentile90.875
Maximum150
Range137.5
Interquartile range (IQR)15.2

Descriptive statistics

Standard deviation23.96433342
Coefficient of variation (CV)0.5876212722
Kurtosis8.324182405
Mean40.78193651
Median Absolute Deviation (MAD)5.9
Skewness2.756585551
Sum1562192.86
Variance574.2892761
MonotonicityNot monotonic
2021-11-29T19:21:27.483702image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
150676
 
0.1%
27.7274
 
< 0.1%
29.8257
 
< 0.1%
28.5255
 
< 0.1%
28.1249
 
< 0.1%
28.6246
 
< 0.1%
27.6244
 
< 0.1%
27.9243
 
< 0.1%
28.2237
 
< 0.1%
28.8235
 
< 0.1%
Other values (1263)35390
 
4.5%
(Missing)751909
95.2%
ValueCountFrequency (%)
12.51
 
< 0.1%
16.61
 
< 0.1%
16.91
 
< 0.1%
17.13
< 0.1%
17.21
 
< 0.1%
17.31
 
< 0.1%
17.41
 
< 0.1%
17.51
 
< 0.1%
17.92
< 0.1%
18.13
< 0.1%
ValueCountFrequency (%)
150676
0.1%
149.91
 
< 0.1%
149.81
 
< 0.1%
149.31
 
< 0.1%
1491
 
< 0.1%
148.91
 
< 0.1%
148.82
 
< 0.1%
148.71
 
< 0.1%
148.51
 
< 0.1%
148.41
 
< 0.1%

WBC
Real number (ℝ≥0)

MISSING

Distinct711
Distinct (%)1.2%
Missing730867
Missing (%)92.5%
Infinite0
Infinite (%)0.0%
Mean11.93660376
Minimum0.1
Maximum422.9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.0 MiB
2021-11-29T19:21:27.760004image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum0.1
5-th percentile4.7
Q18
median10.8
Q314.3
95-th percentile22.1
Maximum422.9
Range422.8
Interquartile range (IQR)6.3

Descriptive statistics

Standard deviation7.56267892
Coefficient of variation (CV)0.6335704084
Kurtosis491.700431
Mean11.93660376
Median Absolute Deviation (MAD)3.1
Skewness13.67031295
Sum708413.56
Variance57.19411244
MonotonicityNot monotonic
2021-11-29T19:21:28.021318image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10.3566
 
0.1%
9.4566
 
0.1%
9.2561
 
0.1%
10561
 
0.1%
11.2554
 
0.1%
8.9554
 
0.1%
10.2552
 
0.1%
9.8551
 
0.1%
9.3551
 
0.1%
9.7551
 
0.1%
Other values (701)53781
 
6.8%
(Missing)730867
92.5%
ValueCountFrequency (%)
0.133
< 0.1%
0.226
< 0.1%
0.320
< 0.1%
0.418
< 0.1%
0.517
< 0.1%
0.614
< 0.1%
0.718
< 0.1%
0.85
 
< 0.1%
0.97
 
< 0.1%
113
 
< 0.1%
ValueCountFrequency (%)
422.91
< 0.1%
375.41
< 0.1%
3421
< 0.1%
322.51
< 0.1%
3161
< 0.1%
242.61
< 0.1%
224.91
< 0.1%
2231
< 0.1%
222.81
< 0.1%
206.31
< 0.1%

Fibrinogen
Real number (ℝ≥0)

MISSING

Distinct759
Distinct (%)12.6%
Missing784185
Missing (%)99.2%
Infinite0
Infinite (%)0.0%
Mean292.2516418
Minimum34
Maximum1760
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.0 MiB
2021-11-29T19:21:28.287629image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum34
5-th percentile114
Q1184
median250
Q3356.75
95-th percentile621
Maximum1760
Range1726
Interquartile range (IQR)172.75

Descriptive statistics

Standard deviation158.6320416
Coefficient of variation (CV)0.5427926449
Kurtosis4.119087026
Mean292.2516418
Median Absolute Deviation (MAD)78
Skewness1.618485195
Sum1762277.4
Variance25164.12463
MonotonicityNot monotonic
2021-11-29T19:21:28.553716image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
18039
 
< 0.1%
21437
 
< 0.1%
20236
 
< 0.1%
21736
 
< 0.1%
18536
 
< 0.1%
19733
 
< 0.1%
18331
 
< 0.1%
20630
 
< 0.1%
23330
 
< 0.1%
18130
 
< 0.1%
Other values (749)5692
 
0.7%
(Missing)784185
99.2%
ValueCountFrequency (%)
341
 
< 0.1%
351
 
< 0.1%
502
 
< 0.1%
521
 
< 0.1%
52.51
 
< 0.1%
562
 
< 0.1%
581
 
< 0.1%
595
< 0.1%
602
 
< 0.1%
611
 
< 0.1%
ValueCountFrequency (%)
17601
< 0.1%
13831
< 0.1%
12462
< 0.1%
11611
< 0.1%
10762
< 0.1%
10512
< 0.1%
10302
< 0.1%
9941
< 0.1%
9791
< 0.1%
9761
< 0.1%

Platelets
Real number (ℝ≥0)

MISSING

Distinct898
Distinct (%)1.7%
Missing738716
Missing (%)93.5%
Infinite0
Infinite (%)0.0%
Mean199.6178411
Minimum5
Maximum1783
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.0 MiB
2021-11-29T19:21:28.831749image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile67.9
Q1127
median181
Q3247
95-th percentile395
Maximum1783
Range1778
Interquartile range (IQR)120

Descriptive statistics

Standard deviation109.2441461
Coefficient of variation (CV)0.547266444
Kurtosis9.324125031
Mean199.6178411
Median Absolute Deviation (MAD)59
Skewness1.969218624
Sum10280119.2
Variance11934.28345
MonotonicityNot monotonic
2021-11-29T19:21:29.107203image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
160271
 
< 0.1%
172271
 
< 0.1%
156263
 
< 0.1%
158263
 
< 0.1%
179263
 
< 0.1%
195261
 
< 0.1%
155260
 
< 0.1%
167258
 
< 0.1%
187258
 
< 0.1%
150255
 
< 0.1%
Other values (888)48876
 
6.2%
(Missing)738716
93.5%
ValueCountFrequency (%)
57
< 0.1%
67
< 0.1%
78
< 0.1%
86
< 0.1%
910
< 0.1%
1010
< 0.1%
10.251
 
< 0.1%
116
< 0.1%
11.51
 
< 0.1%
1210
< 0.1%
ValueCountFrequency (%)
17831
< 0.1%
16671
< 0.1%
15921
< 0.1%
14211
< 0.1%
13431
< 0.1%
13391
< 0.1%
12742
< 0.1%
12621
< 0.1%
12531
< 0.1%
12011
< 0.1%

Age
Real number (ℝ≥0)

Distinct5971
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean63.01677985
Minimum18.11
Maximum89
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.0 MiB
2021-11-29T19:21:29.389504image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum18.11
5-th percentile31.39
Q152.74
median65.25
Q375.89
95-th percentile85.04
Maximum89
Range70.89
Interquartile range (IQR)23.15

Descriptive statistics

Standard deviation16.13363232
Coefficient of variation (CV)0.2560212115
Kurtosis-0.2033869389
Mean63.01677985
Median Absolute Deviation (MAD)11.44
Skewness-0.6192934667
Sum49796804.69
Variance260.2940919
MonotonicityNot monotonic
2021-11-29T19:21:29.650258image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
70.66712
 
0.1%
68.17701
 
0.1%
70.65616
 
0.1%
73.94610
 
0.1%
69.58595
 
0.1%
56.34590
 
0.1%
78.19580
 
0.1%
71.37567
 
0.1%
79.9566
 
0.1%
67561
 
0.1%
Other values (5961)784117
99.2%
ValueCountFrequency (%)
18.1193
< 0.1%
18.1321
 
< 0.1%
18.1475
< 0.1%
18.1518
 
< 0.1%
18.1836
 
< 0.1%
18.2452
< 0.1%
18.3219
 
< 0.1%
18.3448
< 0.1%
18.3542
< 0.1%
18.3618
 
< 0.1%
ValueCountFrequency (%)
8956
 
< 0.1%
88.9940
 
< 0.1%
88.9849
 
< 0.1%
88.97144
< 0.1%
88.9658
 
< 0.1%
88.95144
< 0.1%
88.9465
 
< 0.1%
88.9337
 
< 0.1%
88.92205
< 0.1%
88.9169
< 0.1%

Gender
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size6.0 MiB
1
456524 
0
333691 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters790215
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
1456524
57.8%
0333691
42.2%

Length

2021-11-29T19:21:30.114268image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-11-29T19:21:30.266880image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
1456524
57.8%
0333691
42.2%

Most occurring characters

ValueCountFrequency (%)
1456524
57.8%
0333691
42.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number790215
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1456524
57.8%
0333691
42.2%

Most occurring scripts

ValueCountFrequency (%)
Common790215
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1456524
57.8%
0333691
42.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII790215
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1456524
57.8%
0333691
42.2%

Unit1
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct2
Distinct (%)< 0.1%
Missing386165
Missing (%)48.9%
Memory size6.0 MiB
1.0
204894 
0.0
199156 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters1212150
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0.0
2nd row0.0
3rd row0.0
4th row0.0
5th row0.0

Common Values

ValueCountFrequency (%)
1.0204894
25.9%
0.0199156
25.2%
(Missing)386165
48.9%

Length

2021-11-29T19:21:30.405420image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-11-29T19:21:30.557554image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
1.0204894
50.7%
0.0199156
49.3%

Most occurring characters

ValueCountFrequency (%)
0603206
49.8%
.404050
33.3%
1204894
 
16.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number808100
66.7%
Other Punctuation404050
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0603206
74.6%
1204894
 
25.4%
Other Punctuation
ValueCountFrequency (%)
.404050
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common1212150
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0603206
49.8%
.404050
33.3%
1204894
 
16.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII1212150
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0603206
49.8%
.404050
33.3%
1204894
 
16.9%

Unit2
Categorical

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION
MISSING

Distinct2
Distinct (%)< 0.1%
Missing386165
Missing (%)48.9%
Memory size6.0 MiB
0.0
204894 
1.0
199156 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters1212150
Distinct characters3
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1.0
2nd row1.0
3rd row1.0
4th row1.0
5th row1.0

Common Values

ValueCountFrequency (%)
0.0204894
25.9%
1.0199156
25.2%
(Missing)386165
48.9%

Length

2021-11-29T19:21:30.697010image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-11-29T19:21:30.849187image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
0.0204894
50.7%
1.0199156
49.3%

Most occurring characters

ValueCountFrequency (%)
0608944
50.2%
.404050
33.3%
1199156
 
16.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number808100
66.7%
Other Punctuation404050
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0608944
75.4%
1199156
 
24.6%
Other Punctuation
ValueCountFrequency (%)
.404050
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common1212150
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0608944
50.2%
.404050
33.3%
1199156
 
16.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII1212150
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0608944
50.2%
.404050
33.3%
1199156
 
16.4%

HospAdmTime
Real number (ℝ)

Distinct7152
Distinct (%)0.9%
Missing8
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean-52.02575711
Minimum-3710.66
Maximum23.99
Zeros6308
Zeros (%)0.8%
Negative775386
Negative (%)98.1%
Memory size6.0 MiB
2021-11-29T19:21:30.997880image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum-3710.66
5-th percentile-257.3
Q1-38.09
median-2.6
Q3-0.02
95-th percentile-0.01
Maximum23.99
Range3734.65
Interquartile range (IQR)38.07

Descriptive statistics

Standard deviation155.8649365
Coefficient of variation (CV)-2.99591866
Kurtosis134.2566449
Mean-52.02575711
Median Absolute Deviation (MAD)2.59
Skewness-9.032119427
Sum-41111117.45
Variance24293.87844
MonotonicityNot monotonic
2021-11-29T19:21:31.268456image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-0.02150952
 
19.1%
-0.0390240
 
11.4%
-0.0144460
 
5.6%
-0.0426278
 
3.3%
-0.0512180
 
1.5%
06308
 
0.8%
-0.066004
 
0.8%
-0.073096
 
0.4%
-0.081498
 
0.2%
-0.091215
 
0.2%
Other values (7142)447976
56.7%
ValueCountFrequency (%)
-3710.6656
 
< 0.1%
-3322.943
 
< 0.1%
-3269.121
 
< 0.1%
-3212.5653
 
< 0.1%
-3141.55275
< 0.1%
-2668.7713
 
< 0.1%
-2562.5322
 
< 0.1%
-2506.6937
 
< 0.1%
-2476.5816
 
< 0.1%
-2379.7617
 
< 0.1%
ValueCountFrequency (%)
23.9950
< 0.1%
22.0428
< 0.1%
20.0430
< 0.1%
17.3445
< 0.1%
16.0217
 
< 0.1%
14.6543
< 0.1%
14.2127
< 0.1%
1429
< 0.1%
11.9426
< 0.1%
10.9942
< 0.1%

ICULOS
Real number (ℝ≥0)

HIGH CORRELATION
HIGH CORRELATION
HIGH CORRELATION

Distinct336
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean27.19851812
Minimum1
Maximum336
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.0 MiB
2021-11-29T19:21:31.558868image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q111
median21
Q335
95-th percentile62
Maximum336
Range335
Interquartile range (IQR)24

Descriptive statistics

Standard deviation28.19094028
Coefficient of variation (CV)1.036488097
Kurtosis24.46645459
Mean27.19851812
Median Absolute Deviation (MAD)11
Skewness4.044086828
Sum21492677
Variance794.729114
MonotonicityNot monotonic
2021-11-29T19:21:31.824724image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
820170
 
2.6%
920142
 
2.5%
1020070
 
2.5%
720061
 
2.5%
1120001
 
2.5%
1219918
 
2.5%
619853
 
2.5%
1319824
 
2.5%
1419709
 
2.5%
1519558
 
2.5%
Other values (326)590909
74.8%
ValueCountFrequency (%)
112839
1.6%
216227
2.1%
317905
2.3%
418908
2.4%
519484
2.5%
619853
2.5%
720061
2.5%
820170
2.6%
920142
2.5%
1020070
2.5%
ValueCountFrequency (%)
3369
< 0.1%
3359
< 0.1%
3349
< 0.1%
3339
< 0.1%
3329
< 0.1%
3319
< 0.1%
33010
< 0.1%
32910
< 0.1%
32811
< 0.1%
32711
< 0.1%

SepsisLabel
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size6.0 MiB
0
773079 
1
 
17136

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters790215
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0773079
97.8%
117136
 
2.2%

Length

2021-11-29T19:21:32.095770image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-11-29T19:21:32.248619image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
0773079
97.8%
117136
 
2.2%

Most occurring characters

ValueCountFrequency (%)
0773079
97.8%
117136
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number790215
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0773079
97.8%
117136
 
2.2%

Most occurring scripts

ValueCountFrequency (%)
Common790215
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0773079
97.8%
117136
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII790215
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0773079
97.8%
117136
 
2.2%

Sepsis
Categorical

HIGH CORRELATION

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size6.0 MiB
0
685251 
1
104964 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters790215
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0685251
86.7%
1104964
 
13.3%

Length

2021-11-29T19:21:32.385996image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram of lengths of the category

Pie chart

2021-11-29T19:21:32.538154image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
ValueCountFrequency (%)
0685251
86.7%
1104964
 
13.3%

Most occurring characters

ValueCountFrequency (%)
0685251
86.7%
1104964
 
13.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number790215
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0685251
86.7%
1104964
 
13.3%

Most occurring scripts

ValueCountFrequency (%)
Common790215
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0685251
86.7%
1104964
 
13.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII790215
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0685251
86.7%
1104964
 
13.3%

Hours
Real number (ℝ≥0)

HIGH CORRELATION

Distinct228
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean51.66488994
Minimum8
Maximum336
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.0 MiB
2021-11-29T19:21:32.684618image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Quantile statistics

Minimum8
5-th percentile19
Q136
median44
Q353
95-th percentile132
Maximum336
Range328
Interquartile range (IQR)17

Descriptive statistics

Standard deviation40.95410951
Coefficient of variation (CV)0.7926874433
Kurtosis17.2227095
Mean51.66488994
Median Absolute Deviation (MAD)8
Skewness3.825733184
Sum40826371
Variance1677.239086
MonotonicityNot monotonic
2021-11-29T19:21:32.950127image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3925935
 
3.3%
4125912
 
3.3%
4325800
 
3.3%
4625760
 
3.3%
4425520
 
3.2%
4025360
 
3.2%
3625200
 
3.2%
4225074
 
3.2%
4525065
 
3.2%
3824928
 
3.2%
Other values (218)535661
67.8%
ValueCountFrequency (%)
8992
 
0.1%
91098
 
0.1%
10950
 
0.1%
111254
 
0.2%
121452
 
0.2%
131885
 
0.2%
142716
0.3%
153465
0.4%
164384
0.6%
175916
0.7%
ValueCountFrequency (%)
3361680
0.2%
335335
 
< 0.1%
334334
 
< 0.1%
330330
 
< 0.1%
328328
 
< 0.1%
305610
 
0.1%
297297
 
< 0.1%
286286
 
< 0.1%
279279
 
< 0.1%
277277
 
< 0.1%

Interactions

2021-11-29T19:20:46.791418image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T19:20:34.937108image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T19:20:35.419287image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T19:20:35.973595image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T19:20:36.369820image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T19:20:36.681223image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T19:20:37.091896image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T19:20:37.494667image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T19:20:37.827033image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T19:20:38.236347image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T19:20:38.499649image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T19:20:38.758631image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T19:20:39.019072image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T19:20:39.290134image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T19:20:39.551862image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T19:20:39.799474image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T19:20:40.046552image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T19:20:40.302291image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T19:20:40.540069image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T19:20:40.806527image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T19:20:41.077669image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T19:20:41.329361image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T19:20:41.576665image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T19:20:41.850451image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T19:20:42.095243image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T19:20:42.536111image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T19:20:42.782266image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T19:20:43.053271image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T19:20:43.292197image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T19:20:43.526918image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T19:20:43.831174image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T19:20:44.091133image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T19:20:44.336360image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T19:20:44.592434image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T19:20:44.824412image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T19:20:45.087073image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T19:20:45.516085image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T19:20:45.939163image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
2021-11-29T19:20:46.377964image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Correlations

2021-11-29T19:21:33.287836image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Spearman's ρ

The Spearman's rank correlation coefficient (ρ) is a measure of monotonic correlation between two variables, and is therefore better in catching nonlinear monotonic correlations than Pearson's r. It's value lies between -1 and +1, -1 indicating total negative monotonic correlation, 0 indicating no monotonic correlation and 1 indicating total positive monotonic correlation.

To calculate ρ for two variables X and Y, one divides the covariance of the rank variables of X and Y by the product of their standard deviations.
2021-11-29T19:21:34.294616image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Pearson's r

The Pearson's correlation coefficient (r) is a measure of linear correlation between two variables. It's value lies between -1 and +1, -1 indicating total negative linear correlation, 0 indicating no linear correlation and 1 indicating total positive linear correlation. Furthermore, r is invariant under separate changes in location and scale of the two variables, implying that for a linear function the angle to the x-axis does not affect r.

To calculate r for two variables X and Y, one divides the covariance of X and Y by the product of their standard deviations.
2021-11-29T19:21:35.084899image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Kendall's τ

Similarly to Spearman's rank correlation coefficient, the Kendall rank correlation coefficient (τ) measures ordinal association between two variables. It's value lies between -1 and +1, -1 indicating total negative correlation, 0 indicating no correlation and 1 indicating total positive correlation.

To calculate τ for two variables X and Y, one determines the number of concordant and discordant pairs of observations. τ is given by the number of concordant pairs minus the discordant pairs divided by the total number of pairs.
2021-11-29T19:21:35.768980image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/

Cramér's V (φc)

Cramér's V is an association measure for nominal random variables. The coefficient ranges from 0 to 1, with 0 indicating independence and 1 indicating perfect association. The empirical estimators used for Cramér's V have been proved to be biased, even for large samples. We use a bias-corrected measure that has been proposed by Bergsma in 2013 that can be found here.

Missing values

2021-11-29T19:20:47.423775image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
A simple visualization of nullity by column.
2021-11-29T19:20:52.565725image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2021-11-29T19:21:04.656304image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.
2021-11-29T19:21:07.787511image/svg+xmlMatplotlib v3.4.3, https://matplotlib.org/
The dendrogram allows you to more fully correlate variable completion, revealing trends deeper than the pairwise ones visible in the correlation heatmap.

Sample

First rows

PatientIDlevel_1HRO2SatTempSBPMAPDBPRespEtCO2BaseExcessHCO3FiO2pHPaCO2SaO2ASTBUNAlkalinephosCalciumChlorideCreatinineBilirubin_directGlucoseLactateMagnesiumPhosphatePotassiumBilirubin_totalTroponinIHctHgbPTTWBCFibrinogenPlateletsAgeGenderUnit1Unit2HospAdmTimeICULOSSepsisLabelSepsisHours
010NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN83.140NaNNaN-0.0310054
11197.095.0NaN98.075.33NaN19.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN83.140NaNNaN-0.0320054
21289.099.0NaN122.086.00NaN22.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN83.140NaNNaN-0.0330054
31390.095.0NaNNaNNaNNaN30.0NaN24.0NaNNaN7.36100.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN83.140NaNNaN-0.0340054
414103.088.5NaN122.091.33NaN24.5NaNNaNNaN0.28NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN83.140NaNNaN-0.0350054
515110.091.0NaNNaNNaNNaN22.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN83.140NaNNaN-0.0360054
616108.092.036.11123.077.00NaN29.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN83.140NaNNaN-0.0370054
717106.090.5NaN93.076.33NaN29.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN83.140NaNNaN-0.0380054
818104.095.0NaN133.088.33NaN26.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN83.140NaNNaN-0.0390054
919102.091.0NaN134.087.33NaN30.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN83.140NaNNaN-0.03100054

Last rows

PatientIDlevel_1HRO2SatTempSBPMAPDBPRespEtCO2BaseExcessHCO3FiO2pHPaCO2SaO2ASTBUNAlkalinephosCalciumChlorideCreatinineBilirubin_directGlucoseLactateMagnesiumPhosphatePotassiumBilirubin_totalTroponinIHctHgbPTTWBCFibrinogenPlateletsAgeGenderUnit1Unit2HospAdmTimeICULOSSepsisLabelSepsisHours
790205206432386.088.0NaN132.079.061.016.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN62.291NaNNaN-0.03260133
7902062064324131.098.0NaN142.083.065.016.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN62.291NaNNaN-0.03271133
7902072064325118.098.038.11124.081.063.016.0NaNNaNNaN0.4NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN62.291NaNNaN-0.03281133
7902082064326NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN62.291NaNNaN-0.03291133
7902092064327NaNNaNNaNNaNNaNNaNNaNNaNNaNNaN0.5NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN62.291NaNNaN-0.03301133
790210206432888.098.0NaN135.081.064.016.0NaNNaNNaN0.5NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN62.291NaNNaN-0.03311133
790211206432996.098.038.72174.097.072.016.0NaN2.0NaNNaN7.4834.097.090.026.0107.0NaNNaN2.5NaNNaNNaN2.23.53.90.9NaN27.8NaNNaNNaNNaNNaN62.291NaNNaN-0.03321133
7902122064330140.097.0NaN133.081.562.516.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN62.291NaNNaN-0.03331133
7902132064331120.096.0NaN154.0118.0105.016.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN62.291NaNNaN-0.03341133
7902142064332115.095.0NaN150.0117.0104.016.0NaNNaNNaNNaNNaNNaN98.0NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN62.291NaNNaN-0.03351133